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Record W2363080379

The change of land use/cover in Shulehe River

2012· article· en· W2363080379 on OpenAlexaff
Sun Liwei

Bibliographic record

VenueGanhanqu ziyuan yu huanjing · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Ecology and Soil Science
Canadian institutionsScience North
Fundersnot available
KeywordsLand useGrasslandLand coverLand use, land-use change and forestryLand developmentPhysical geographyEnvironmental scienceGeographyEnvironmental changeHydrology (agriculture)Cultivated landGlobal changeClimate changeEcologyGeology
DOInot available

Abstract

fetched live from OpenAlex

Land use and cover changes(LUCC) are not only one of the core issues of global change but also play a critical role in eco-environment construction,global environmental change and sustainable development.Land use and cover changes are the most prominent in the Shulehe River as a whole.Due to being located in an environmentally and regionally sensitive region,the Shulehe River has become a hot area regarding land use and cover change.In the present paper,the authors performed a study on LUCC over the Shulehe River,during the period 1990-2010 using Landsat TM images and GIS and Land-use Dynamic Degree techniques.In particular,the authors quantified changes in different kinds of land use types and analyzed their spatial variation trends and characteristics.Results are shown as follows.First,It was found that from 1990 to 2010,overall land use characteristics of the Shulehe River changed slightly,but the internal structure for each kind of land use types changed significantly.Unused land,Grassland and cultivated land were always major land use types during the 20 years,occupying approximately 98.22% of the total area,respectively.Second,from 1990 to 2010,most of land use changes occurred in cultivated land,built-up land and grassland,the velocities of land use changes were 13.60%,7.97%,7.68%,respectively.Third,LUCC is indeed a complex system,which is affected by many factors interrelated with each other,including both socio-economic and natural environment factors.Major driving forces for land use and cover change in the Shulehe River were probably considered policy and population growth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.229
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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